code: def val_dataloader(self):
      return DataLoader(self.mnist_val, batch_size=32)
  
imports: from __future__ import annotations
  import pytorch_lightning
  import torch
  import torch.nn.functional
  from torch.optim.lr_scheduler import ExponentialLR
  from torch.utils.data import random_split, DataLoader
  from torchmetrics.functional import accuracy
  from torchvision.datasets import MNIST
  from torchvision import transforms
  import nni
  from .simple_torch_model import SimpleTorchModel
label_desc: Use image node_id 5 for calling the MNISTDataModule obj's underlying member method code with example usage: obj.val_dataloader() and returns: DataLoader